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Designing agent infrastructure that scales with context

As agents handle longer workflows, context becomes an infrastructure problem. We explore how persistence, retrieval, and execution state can work together without overwhelming the model.

Mekhos AI Labs·August 2026·8 min read
Designing agent infrastructure that scales with context

Why context becomes an infrastructure problem

Long-running agents accumulate information quickly. Without a clear strategy for managing that information, context becomes increasingly expensive and difficult to reason about.

Separating state from knowledge

A scalable architecture needs to separate execution state from persistent knowledge while still making relevant information available when an agent needs it.

Keeping context useful

Our infrastructure work focuses on keeping context useful rather than simply making it larger, with explicit boundaries between transient state, durable memory, retrieval results, and task-specific information.